for the math homies, you could say that NaN is an absorbing element
Yoko, Shinobu ni, eto… 🤔
עַם יִשְׂרָאֵל חַי Slava Ukraini 🇺🇦 ❤️ 🇮🇱
for the math homies, you could say that NaN is an absorbing element
Omae wa mou shindeiru
The tone may be a bit harsh but it’s muuuuch better than how he used to be during his most toxic days. This is how he used to talk: https://www.networkworld.com/article/706908/security-torvalds-to-bad-security-devs-kill-yourself-now.html
Linus definitely got much better at handling his anger since his public apology in 2018.
Yeah it’s not Linux. It’s forked off MenuetOS (https://menuetos.net/ ) which is a hobby OS written entirely in assembly (FASM flavor, https://flatassembler.net/ ).
It’s actually a good thing that visual learners get a chance to learn useful stuff by watching videos. Not everyone has the attention span required to read through a Wikipedia page.
I already got functional laptops (an Alienware M15 r3 and a very recent HP Pavilion) but none of them come close to my Thinkpad T480 in terms of comfort of use, the overall build quality and the damn awesome keyboard.
Too bad that all (?) recent Thinkpads now have soldered RAM.
lacks an anime girl wallpaper IMO
I’d call the cops on them
Lemmy seems like a nice person, even helping with bootloader unlocking and stuff
For anyone wondering what Proton GE is, it’s Proton on steroids: https://github.com/GloriousEggroll/proton-ge-custom
For instance, even if you have an old Intel integrated GPU, chances are you can still benefit from AMD’s FSR just by pushing a few flags to Proton GE, even if the game doesn’t officially support it, and you’ll literally get a free FPS boost (tested it for fun and can confirm on an Intel UHD Graphics 620).
Congrats! Your laptop will be even happier with a lighter but still nice-looking desktop environment like Xfce and you even have an Ubuntu flavor around it: Xubuntu.
reminds me of instead of
#if !defined(...)
TIL!
and it’s mobile-friendly and distraction-free too
With how MS Teams and now CNN have been reported here to be blocking Firefox, you know that Firefox is doing things right. If web giants are ganging up against it, it’s all the more reason to switch to it to make a statement and prevent big tech from making privacy violation the norm.
Hard to tell as it’s really dependent on your use. I’m mostly writing my own kernels (so, as if you’re doing CUDA basically), and doing “scientific ML” (SciML) stuff that doesn’t need anything beyond doing backprop on stuff with matrix multiplications and elementwise nonlinearities and some convolutions, and so far everything works. If you want some specific simple examples from computer vision: ResNet18 and VGG19 work fine.
Works out of the box on my laptop (the export
below is to force ROCm to accept my APU since it’s not officially supported yet, but the 7900XTX should have official support):
Last year only compiling and running your own kernels with hipcc
worked on this same laptop, the AMD devs are really doing god’s work here.
Yup, it’s definitely about the “open-source” part. That’s in contrast with Nvidia’s ecosystem: CUDA and the drivers are proprietary, and the drivers’ EULA prohibit you from using your gaming GPU for datacenter uses.
ROCm is that its very unstable
That’s true, but ROCm does get better very quickly. Before last summer it was impossible for me to compile and run HIP code on my laptop, and then after one magic update everything worked. I can’t speak for rendering as that’s not my field, but I’ve done plenty of computational code with HIP and the performance was really good.
But my point was more about coding in HIP, not really about using stuff other people made with HIP. If you write your code with HIP in mind from the start, the results are usually good and you get good intuition about the hardware differences (warps for instance are of size 32 on NVidia but can be 32 or 64 on AMD and that makes a difference if your code makes use of warp intrinsics). If however you just use AMD’s CUDA-to-HIP porting tool, then yeah chances are things won’t work on the first run and you need to refine by hand, starting with all the implicit assumptions you made about how the NVidia hardware works.
HIP is amazing. For everyone saying “nah it can’t be the same, CUDA rulez”, just try it, it works on NVidia GPUs too (there are basically macros and stuff that remap everything to CUDA API calls) so if you code for HIP you’re basically targetting at least two GPU vendors. ROCm is the only framework that allows me to do GPGPU programming in CUDA style on a thin laptop sporting an AMD APU while still enjoying 6 to 8 hours of battery life when I don’t do GPU stuff. With CUDA, in terms of mobility, the only choices you get are a beefy and expensive gaming laptop with a pathetic battery life and heating issues, or a light laptop + SSHing into a server with an NVidia GPU.
There’s also group C which I was part of, you just say that you just pooped or scratch your butt whenever they ask you to load/unload and they’ll immediately offer to do that for you instead.